| 基于DE—BP神经网络的刀具寿命预测研究 |
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| 引用本文： | 于青,王金林.基于DE—BP神经网络的刀具寿命预测研究[J].机床与液压,2009,37(4). |
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| 作者姓名： | 于青 王金林 |
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| 作者单位： | 1. 天津理工大学计算机科学与技术学院,天津,300191;天津市智能计算及软件新技术重点实验室,天津,300191
2. 天津大学电子信息工程学院,天津,300072 |
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| 基金项目： | 天津市科技支撑计划项目 |
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| 摘 要： | 引入了BP神经网络技术对刀具寿命进行预测,建立了刀具寿命预测模型.并针对BP神经网络所存在的缺陷,结合差异演化算法,提出了实数编码的DE-BP神经网络预测模型.实验表明,该模型对刀具寿命预测精度高,为刀具需求计划制定、成本核算、切削参数制定提供了理论依据,节约了制造执行系统成本.
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| 关 键 词： | 神经网络 差异演化算法 预测 刀具寿命 |
Prediction of Cutting Tool Life Based on DE-BP Algorithm |
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| YU Qing,WANG Jinlin.Prediction of Cutting Tool Life Based on DE-BP Algorithm[J].Machine Tool & Hydraulics,2009,37(4). |
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| Authors: | YU Qing WANG Jinlin |
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| Affiliation: | YU Qing1,2,WANG Jinlin3(1.School of Computer Science and Technology,Tianjin University of Technology,Tianjin 300191,China,2.Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology,3.School of Electronic and Information Engineering,Tianjin University,Tianjin 300072,China) |
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| Abstract: | Artificial neural network was introduced into the prediction of cutting tool life.Aimed at the drawback in classical BP artificial networks and combined with differential evolution algorithms,the prediction model based on real number coded DE-BP artificial networks was put forward.The result shows that the prediction model has high precision in predicting the cutting tool life,it can be used to establish the cutting tool requirement planing,calculate the cost and select the machining parameters. |
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| Keywords: | Neural network Differential evolution Prediction Cutting tool life |
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